The assimilation of spectral sensing and the WOFOST model for the dynamic simulation of cadmium accumulation in rice tissues

Wu, Ling; Liu, Xiangnan; Wang, Ping; Zhou, Botian; Liu, Meiling; Li, Xuqing

doi:10.1016/j.jag.2013.04.002

Cited by 39 publications

(33 citation statements)

References 25 publications

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“…Wu et al, 2013 embedded four factors into the crop growth model, respectively, corresponding to roots, stems, leaves, and seeds, in which the number of stress factors was usually larger than the number of usable remote sensing images in a specified area throughout a growth cycle; under these conditions, over-parameterization of stress factors will occur, leading to incorrect results. In this study, the WOFOST model was improved by incorporating two stress factors corresponding to two important physiological indicators (assimilation rate and carbohydrate-to-dry matter conversion coefficient) of crops.…”

Section: Discussionmentioning

confidence: 99%

An improved assimilation method with stress factors incorporated in the WOFOST model for the efficient assessment of heavy metal stress levels in rice

Jin

Liu

et al. 2015

International Journal of Applied Earth Observation and Geoinfor

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Section: Discussionmentioning

confidence: 99%

An improved assimilation method with stress factors incorporated in the WOFOST model for the efficient assessment of heavy metal stress levels in rice

Jin

Liu

et al. 2015

International Journal of Applied Earth Observation and Geoinfor

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“…The improved WOFOST model and assimilation is described in detail with reference to previous studies [3,5,40].…”

Section: Lai Assimilation Into the Wofost Modelmentioning

confidence: 99%

“…One of the major problems is heavy metal pollution of paddy fields, which is the widely cultivated crop in China and provided approximately 42% of the national grain reserves [1][2][3][4]. The accumulation of heavy metal ions in rice can threaten food security and harm human health.…”

Section: Introductionmentioning

confidence: 99%

Estimating FAPAR of Rice Growth Period Using Radiation Transfer Model Coupled with the WOFOST Model for Analyzing Heavy Metal Stress

Zhou¹,

Liu²,

Zhao³

et al. 2017

Remote Sensing

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Timely assessment of crop growth conditions under heavy metal pollution is of great significance for agricultural decision-making and estimation of crop productivity. The object of this study is to assess the effects of heavy metal stress on physiological functions of rice through the spatial-temporal analysis of the fraction of absorbed photosynthetically active radiation (FAPAR). The calculation of daily FAPAR is conducted based on a coupled model consisting of the leaf-canopy radiative transfer model and World Food Study Model (WOFOST). These two models are connected by leaf area index (LAI) and a fraction of diffused incoming solar radiation (SKYL) in the rice growth period. The input parameters of the coupled model are obtained from measured data and GF-1 images. Meanwhile, in order to improve accuracy of FAPAR, the crop growth model is optimized by data assimilation. The validation result shows that the correlation between the simulated FAPAR and the measured data is strong in the rice growth period, with the correlation coefficients being above 7.5 for two areas. The discrepancy of FAPAR between two areas of different stress levels is visualized by spatial-temporal analysis. FAPAR discrepancy starts to appear in the jointing-booting period and experiences a gradual rise, reaching its maximum in the heading-flowering stage. This study suggests that the coupled model, consisting of the leaf-canopy radiative transfer model and the WOFOST model, is able to accurately simulate daily FAPAR during crop growth period and FAPAR can be used as a potential indicator to reflect the impact of heavy metal stress on crop growth.

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“…Two rice-growing areas ( Fig. 1) were categorized as "safe level" and "stress level" based on the measured soil Cd concentrations in the sample plots (Table I) [13]. The study areas are approximately 12 km away from each other and have similar climate, historical land use, and soil series.…”

Section: A Study Areamentioning

confidence: 99%

“…However, the use of only remote sensing or spectral measurement focuses on the stress-induced changes to the aerial organs of plants, whereas monitoring of Cd stress in roots has been ignored. Most of the previous algorithms and models were established based on the relationships between sensitive spectral characteristics and heavy metal concentrations or crop growth parameters [7]- [13]. These relationships were generally based on the statistical analysis of the leaflevel spectral reflectance from the plants that were exposed to varying levels of heavy metal stress.…”

mentioning

confidence: 99%

The Dynamic Assessment Model for Monitoring Cadmium Stress Levels in Rice Based on the Assimilation of Remote Sensing and the WOFOST Model

Liu

Zhao

et al. 2015

IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing

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Monitoring of heavy metal stress in crops is vital for food security and agricultural production management. Traditional remote sensing methods focus on the stress-induced changes to the aerial organs of plants, whereas roots are considered to be more directly and severely stressed. In this study, the dry weight of rice roots (WRT) was used as an indicator for monitoring cadmium (Cd) stress levels in rice tissues. The World Food Study (WOFOST) model is a widely used analysis tool for describing the fundamental processes of crop growth, and has been tested for similar applications. We used this model to incorporate a Cd stress factor (fCd), allowing us to simulate the WRT values more accurately. Then, an optimized method of assimilating remotely sensed leaf area index (LAI) into the modified WOFOST model was used to optimize the simulation process and obtain the optimum value of f Cd. Thus, the dynamic simulation of WRT under Cd stress was adjusted. Based on the WRT values of two sample plots with different soil Cd concentrations, the ratio between them (WRTStress/WRTSafe) was calculated subsequently. The variation in the ratio curve generally reflected the stress mechanism in time scale, indicating that the dynamic simulation of WRT was reliable. This study suggests that the method of assimilating remote sensing data into the crop growth model is applicable for simulating crop growth under Cd stress on spatial-time scale, providing a reference for dynamically monitoring heavy metal contamination in rice tissues.

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The assimilation of spectral sensing and the WOFOST model for the dynamic simulation of cadmium accumulation in rice tissues

Cited by 39 publications

References 25 publications

An improved assimilation method with stress factors incorporated in the WOFOST model for the efficient assessment of heavy metal stress levels in rice

An improved assimilation method with stress factors incorporated in the WOFOST model for the efficient assessment of heavy metal stress levels in rice

Estimating FAPAR of Rice Growth Period Using Radiation Transfer Model Coupled with the WOFOST Model for Analyzing Heavy Metal Stress

The Dynamic Assessment Model for Monitoring Cadmium Stress Levels in Rice Based on the Assimilation of Remote Sensing and the WOFOST Model

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